The reduced number of dimensions from MDS solutions with natural stimuli should reflect reliance on a few salient dimensions at the cost of the not-as-salient ones. A particular dimension should not necessarily reveal itself in the solution if several other dimensions have already been relied upon by listeners to differentiate the stimuli in the set. Thus, even though the dimension is something that could potentially distinguish instruments in the set, it may not be sufficiently strong to contribute to a particular solution (i.e., for a particular stimulus set).
Much of the ânoiseâ from MDS solutions can come not only from stimulus uncertainty (e.g., when using a larger number of stimuli, or a set that shares a greater degree of shared acoustic variation across stimuli), but also from how the task is implemented. Because of the large number of trials required to represent every pair in the set, it is common for researchers to greatly limit the number of repetitions of each pair. It is not unusual to see an MDS study with only 2 or 3 repetitions of a given pair. This means that any 1 response can greatly impact average ratings for a given stimulus pair, even if that response followed a trial where the listener was momentarily not attending as well to one or both of the stimuli.
Another concern with reliance on MDS solutions with natural tokens is in the correlational procedure used to determine the dimensions. Acoustic dimensions often covary, which could produce misleading information about the critical dimensions of timbre. For example, in a paper under review, Jim Beauchamp and I recently instead used identification and discrimination tasks to reveal that listeners rely on an understanding of spectral envelope shape (through a manipulation of formant structure) rather than on brightness alone (presumably indicated by spectral centroid variation, which was manipulated in our study by filtering). Yet, it is common for researchers to talk about listenersâ reliance on brightness based on a strong correlation with spectral centroid variation in an MDS solution, even though other, earlier work has shown even stronger predictions of performance based on spectral envelope shape.
What I am suggesting is a need to identify the relevant covariates. If a particular dimension contributes to one solution, but not another, that can tell us that they are either related/redundant, or alternatively, differ in salience, or both. It is then relatively straightforward to put any related dimensions in competition with each other (e.g., under more tightly controlled stimulus conditions) to determine which is more generally relied upon in assessing instrument timbre.
Sincerely,
Michael Hall
Department of Psychology
James Madison University
Michael Hall
Department of Psychology
MSC 7704
James Madison University
Harrisonburg, VA 22807
office: (540) 568-7877
fax: (540) 568-3322